AI/ML Architect

AI/ML Architect

Experience: 8+ Years
Location: Remote – Pan India
Working Hours: 11:00 AM – 9:00 PM IST

Job Summary

We are looking for a highly experienced and hands-on AI/ML Architect to design, develop, and deliver scalable Artificial Intelligence, Machine Learning, and Generative AI solutions for enterprise applications.

The ideal candidate will have strong expertise in AI/ML architecture, Python, Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, cloud platforms, MLOps, and LLMOps.

This is a hands-on technical leadership role requiring the ability to take AI solutions from architecture and development through deployment, evaluation, monitoring, and production operationalization.

Key Responsibilities

• Design and architect end-to-end AI, ML, and Generative AI solutions for enterprise use cases.
• Translate business and technical requirements into scalable, secure, reliable, and production-ready AI architectures.
• Develop production-grade AI/ML applications using Python, APIs, AI/ML frameworks, and cloud services.
• Design and implement solutions using LLMs, RAG, embeddings, vector databases, vector search, and Agentic AI.
• Develop AI applications that integrate with enterprise systems, APIs, data platforms, and business applications.
• Design solutions for model training, fine-tuning, inference, deployment, evaluation, monitoring, and lifecycle management.
• Implement MLOps and LLMOps practices across the AI development lifecycle.
• Build CI/CD pipelines and automated testing processes for AI/ML and GenAI applications.
• Implement model versioning, prompt versioning, experiment tracking, evaluation, observability, and monitoring.
• Evaluate and optimize AI solutions for accuracy, latency, scalability, reliability, and cost.
• Ensure AI solutions meet enterprise requirements for security, privacy, Responsible AI, governance, and compliance.
• Work with structured and unstructured data, data pipelines, enterprise data platforms, and knowledge sources.
• Conduct code reviews, troubleshoot complex technical issues, and drive engineering best practices.
• Provide technical leadership and mentorship to AI/ML engineers and development teams.
• Collaborate with architects, engineering teams, product managers, business stakeholders, and leadership teams.

Required Skills & Experience

• 8+ years of experience in AI/ML engineering, architecture, software development, or enterprise AI solution delivery.
• Strong hands-on development experience with Python.
• Strong expertise in Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI.
• Strong hands-on experience with Large Language Models (LLMs).
• Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
• Strong understanding of:
• Embeddings
• Vector databases
• Vector search
• Prompt engineering
• Context engineering
• LLM evaluation
• Hands-on experience with Agentic AI and AI/model orchestration frameworks.
• Experience with at least one major cloud platform:
• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)
• Strong understanding of MLOps and LLMOps.
• Experience with:
• CI/CD
• Model deployment
• Model monitoring
• Automated testing
• Containers
• APIs
• Microservices
• Observability
• Experience working with structured and unstructured data, data pipelines, and enterprise data platforms.
• Strong understanding of AI security, data privacy, Responsible AI, governance, and enterprise AI architecture.
• Strong understanding of software engineering principles, scalable architecture, and production deployment practices.
• Excellent communication, stakeholder management, analytical, and problem-solving skills.

Good to Have

• Experience with fine-tuning, model adaptation, or parameter-efficient fine-tuning (PEFT).
• Experience with AI agents, tool calling, function calling, and multi-agent workflows.
• Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, or Azure AI Search.
• Experience with AI/ML platforms and frameworks such as LangChain, LangGraph, LlamaIndex, MLflow, or similar technologies.
• Experience with LLM evaluation frameworks and AI observability.
• Experience with Kubernetes and Docker.
• Experience designing highly scalable …